AI Breast Cancer Detection Platform. Vision AI Medical Imaging Software

Customer Stories

A digital healthcare platform that incorporates Vision AI for mammography and ultrasound medical imaging analysis for breast cancer detection.

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Healthcare

Industry

Canada

Location

AI/ML Engineering, Cloud Infrastructure, Medical Image Annotation

Services

Confidential

Budget

Blackthorn.ai’s work is amazing, and the results have been phenomenal and satisfy my expectations.

Under NDA

Executive, Healthcare Company

Challenge

A radiologist’s diagnosis is subjective and often inaccurate, leading to up to 30% errors. Patients suffer repeated visits to hospitals, anxiety about diagnosis delays, and false radiologist conclusions.

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Outcomes We Deliver

Solution

Our team designed and developed an AI-powered medical imaging analysis platform that, when paired with a radiologist, increased breast cancer detection accuracy by 20-30% in clinical trials compared to a radiologist alone.

Let’s talk about what’s possible

Tech Stack

To deliver a full AI-powered diagnostic platform combining mammography and ultrasound workflows, Blackthorn AI applied:

Python

Fast API

OpenAI

TypeScript

JavaScript

PyTorch

Terraform

Azure

Docker

Python

Fast API

OpenAI

TypeScript

JavaScript

PyTorch

Terraform

Azure

Docker

Roadmap

Project duration

01 Month

Planning & architecture

Finalized system architecture and aligned platform vision with the client; approved detailed implementation roadmap.

02 Month

AI pipeline deployment

Deployed the mammogram AI pipeline on Azure and connected public dataset inference models to the pipeline.

03 Month

Annotation strategy & data prep

Designed ultrasound annotation strategy; completed and validated annotation for the first batch of 100 images.

04 Month

Dual-model development

Built classification model combining mammogram + ultrasound data; performed testing and initial validation.

05 Month

Web + API deployment

Deployed models via web interface and APIs for clinical use; integrated frontend and backend components.

06 Month

QA docs & handoff

Ran full QA cycle; delivered final documentation and support for onboarding client’s internal teams.

01 Month

Planning & architecture

Finalized system architecture and aligned platform vision with the client; approved detailed implementation roadmap.

02 Month

AI pipeline deployment

Deployed the mammogram AI pipeline on Azure and connected public dataset inference models to the pipeline.

03 Month

Annotation strategy & data prep

Designed ultrasound annotation strategy; completed and validated annotation for the first batch of 100 images.

04 Month

Dual-model development

Built classification model combining mammogram + ultrasound data; performed testing and initial validation.

05 Month

Web + API deployment

Deployed models via web interface and APIs for clinical use; integrated frontend and backend components.

06 Month

QA docs & handoff

Ran full QA cycle; delivered final documentation and support for onboarding client’s internal teams.

Team Size

1 x AI Solution Architect

1 x Machine Learning Engineer

4 x Radiologist Consultant

4 x Annotator Specialists

3 x Computer Vision Engineer

1 x Backend Engineer

1 x DevOps Engineer

1 x Frontend Developer

1 x Project Manager

16 Qualified AI Experts

1 x AI Solution Architect

1 x Machine Learning Engineer

4 x Radiologist Consultant

4 x Annotator Specialists

3 x Computer Vision Engineer

1 x Backend Engineer

1 x DevOps Engineer

1 x Frontend Developer

1 x Project Manager

Delivering Impact

Book a Meeting

+ 21%

Diagnostic accuracy

Radiologist assisted by AI vs. radiologist alone

< 1 min

Instant AI diagnosis

Near-instant, AI-generated second opinion for clinicians

+ 21%

Diagnostic accuracy

Radiologist assisted by AI vs. radiologist alone

< 1 min

Instant AI diagnosis

Near-instant, AI-generated second opinion for clinicians

AI Breast Cancer Detection Platform

A digital healthcare platform that incorporates Vision AI for mammography and ultrasound medical imaging analysis for breast cancer detection.

Healthcare

Canada

AI/ML Engineering, Cloud Infrastructure, Medical Image Annotation

Confidential

A radiologist’s diagnosis is subjective and often inaccurate, leading to up to 30% errors. Patients suffer repeated visits to hospitals, anxiety about diagnosis delays, and false radiologist conclusions.

Solution

To deliver a full AI-powered diagnostic platform combining mammography and ultrasound workflows, Blackthorn AI applied:

Project duration

01 Month

02 Month

03 Month

04 Month

05 Month

06 Month

01 Month

02 Month

03 Month

04 Month

05 Month

06 Month

Team Size

Delivering Impact

+ 21%

< 1 min

+ 21%

< 1 min

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